Job Description - Masterand (all genders) - Design of Explanation Interfaces in AI in Healthcare
The integration of Artificial Intelligence (AI) based decision support systems (DSS) into clinical settings holds considerable promise for aiding complex decision-making and enhancing patient care. Despite their potential, the practical implementation of such AI systems has been limited due to clinicians’ caution, often attributed to a lack of acceptance and trust.
Utilizing Explainable AI (XAI) methods can be a great tool to open the “black-box” and provide human-understandable explanations. Finding appropriate visualizations of explanations will be pivotal to enhance the understandability and thus fostering trust, transparency and human-oversight in AI-based DSS.
You will research various current concepts for visualizing explanations of AI predictions (XUI - Explanation User Interface).
You will bring together the different requirements of clinical staff, end users and software developers in innovative functional concepts.
You will evaluate established design concepts in literature and create new design concepts to visualize explanations for AI predictions.
You will conduct user testing on clinical staff and work with AI researchers to establish human-centered AI in hospitals.
You like to explore new creative, technological and social topics, enjoy technical issues and actively shape the processes in your environment.
Depending on your interests and abilities, you choose the direction of your work.
You are studying communication design, interactive media or a similar course.
You are interested in the fields of information design, data visualization and usability design.
You don't shy away from technical discussions about data science and AI.
You work independently and in a self-organized manner, and you proactively contribute to the team.
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